Abstract : We present a novel semantics for extracting bounded-level modules from RDF ontologies and databases augmented with safe inference rules, a la Datalog. Dealing with a recursive rule language poses challenging issues for defining the module semantics, and also makes module extraction algorithmically unsolvable in some cases. Our results include a set of module extraction algorithms compliant with the novel semantics. Experimental results show that the resulting framework is effective in extracting expressive modules from RDF datasets with formal guarantees, whilst controlling their succinctness.
https://hal-lirmm.ccsd.cnrs.fr/lirmm-01086951
Contributor : Federico Ulliana
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Submitted on : Thursday, January 15, 2015 - 10:02:37 AM
Last modification on : Saturday, June 29, 2019 - 5:30:48 PM
Long-term archiving on : Friday, September 11, 2015 - 6:49:06 AM
Marie-Christine Rousset, Federico Ulliana. Extracting Bounded-level Modules from Deductive RDF Triplestores. AAAI Conference on Artificial Intelligence, Jan 2015, Austin, TX, United States. ⟨lirmm-01086951⟩
